A cyber-physical attack in the industrial Internet of Things can cause severe damage to physical system. In this paper, we focus on the command disaggregation attack, wherein attackers modify disaggregated commands by intruding command aggregators like programmable logic controllers, and then maliciously manipulate the physical process. It is necessary to investigate these attacks, analyze their impact on the physical process, and seek effective detection mechanisms. We depict two different types of command disaggregation attack modes: (1) the command sequence is disordered and (2) disaggregated sub-commands are allocated to wrong actuators. We describe three attack models to implement these modes with going undetected by existing detection methods. A novel and effective framework is provided to detect command disaggregation attacks. The framework utilizes the correlations among two-tier command sequences, including commands from the output of central controller and sub-commands from the input of actuators, to detect attacks before disruptions occur. We have designed components of the framework and explain how to mine and use these correlations to detect attacks. We present two case studies to validate different levels of impact from various attack models and the effectiveness of the detection framework. Finally, we discuss how to enhance the detection framework.
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